Adam Ferguson, MS, PhD

Adam Ferguson’s research interests span from mechanistic neuroscience in model organisms to large-scale clinical data science and precision medicine research for TBI and SCI. He directs a diverse team of researchers performing a hybrid of bench neuroscience in the laboratory and translational data science, supported by grants from the NIH, VA, DoD, DARPA, and nonprofits. He has served in leadership roles in the National Neurotrauma Society as an elected Councilor, Secretary/Treasurer, and Vice President (2023 term) and President (2024 term). His community and public service roles include serving as founding co-director of international data sharing efforts in neurotrauma through the Open Data Commons for SCI (odc-sci.org) and TBI (odc-tbi.org); representing the field of neurotrauma at the National Academies of Sciences, Engineering, and Medicine workshops on the data lifecycle in biomedicine; serving on NIH/NINDS TBI common data elements workgroups; and federal study sections. He also has a strong dedication to teaching and mentorship of next-generation researchers. He serves as curriculum co-director for data science and biostatistics for the UCSF Biomedical Sciences graduate program and has served as sponsor/mentor on 16 successful fellowships including 5 NIH NRSAs, a K99R00, an K22R00, an NIH diversity supplement, NIH BD2K RoadTrip fellowship, VA Career Development awards, among others. He has published 180+ peer-reviewed papers with trainees from diverse and multidisciplinary backgrounds across bench science, data science, and clinical neurotrauma research.

Brain and Spinal Injury Center

UCSF Brain and Spinal Injury Center

1001 Potrero Ave,  Bldg 1, Rm 101
San Francisco, CA 94143

Email: [email protected]

Phone: (628) 206-3734

Fax: (628) 206-3948

Research

Background: Our research focuses on mechanisms of recovery after neurological trauma. Injuries to the brain and spinal cord invoke numerous, interacting biological processes that work in concert to determine recovery success. Some of these biological processes have contradictory effects at different phases of recovery. For example, mechanisms of synaptic regulation can contribute to cell death in the early phases of recovery but may promote plasticity and restoration of function at later stages.  Understanding the mechanisms of recovery in the complex microenvironment of the injured central nervous system (CNS) requires large-scale integration of biological information and functional outcomes (i.e., Data Science). Our work uses a combination of laboratory studies and statistical modeling approaches to provide an information-rich picture of the syndrome produced by trauma in translational in vivo models.  The long term goal of this research is to provide system-level therapeutic targets for enhancing recovery of function after brain and spinal injury.

Overarching goal: Understand and harness CNS plasticity to promote recovery of function after brain and spinal cord injury through bench-science and translational computational approaches.

Ongoing Research:

Computational Syndromic Discovery: Development of aggregate databases of basic spinal cord injury and traumatic brain injury research data from multiple research centers to enable sophisticated knowledge-discovery, data-sharing, and multivariate quantification of the complete constellation of changes produced by neurotrauma.

Bench science: Inflammatory modulation of glutamate-receptor metaplasticity and its role in spinal cord learning and recovery of function after neurotrauma. Techniques: biochemistry (quantitative western, qRT-PCR, ELISA), histology (immunohistochemistry, in situ hybridization), quantitative image analysis (robotic microscopy, confocal, deconvolution, image math) and behavioral analysis (locomotor scaling, fine-motor control, learning and memory).

Primary Thematic Area:  Neurobiology

Secondary Thematic Area:  Immunology

Research Summary: CNS Plasticity, Data Science, and Recovery from Injury

Funding

We are funded through a variety of research grants from the NIH, DoD, DARPA, DoE, NIDILRR, the VA, Wings for Life Foundation, Craig H. Neilsen Foundation, and other non-profit foundations.

• R01: Maladaptive Plasticity in Spinal Cord Injury: Cellular Mechanisms
• R01: Dopamine Modulation for the Treatment of Chronic Dysfunction Due to Traumatic Brain Injury
• R01: The Primate Corticospinal Connectome and Transcriptome
• R01: Bioinformatics for post-traumatic stress
• U24: Pan-Neurotrauma Data Commons
• U24: Enhancing the Pan-Neurotrauma Data Commons (PANORAUMA) to a complete open data science tool by FAIR APIs
• UH3: Translational Outcomes Project: Visualizing Syndromic Information and Outcomes for Neurotrauma (TOP-VISION)
• U19: UCSF Core Center for Patient-centric Mechanistic Phenotyping in Chronic Low Back Pain (UCSF REACH)
• Wings for Life: Elevating SCI Translation: Combining Literature-sourced Informatics, Meta-science, Bioinformatics Evidence Research (CLIMBER)
• Wings for Life/Craig H. Neilsen Foundation/ISRT prime: Facilitating SCI Research, Translation, and Transparency: Going Public with the Open Data Commons
• DoD:
  • Tele-psychology Intervention for Individuals with Spinal Cord Injury and Depression
  • Transforming Research Clinical Knowledge in Spinal Cord Injury: TRACK-SCI
  • Advancing Artificial Intelligence (AI) Toward Precision Medicine in Traumatic Brain Injury: A Proposed Collaboration by the US Department of Health Affairs (DHA), US Department of Energy (DoE), TRACK-TBI, and the CARE Consortium
  • Using Big-Data and Machine Learning Approaches to Discover Prognostic Biomarkers and Drugs for Neuropathic Pain in Chronic SCI
• VA:
  • Harnessing big-data for plasticity and rehabilitation in translational SCI
  • Leveraging Data Science for Discovery in Chronic TBI
  • PRECISE-TBI: PRE Clinical Interagency research resourcE-TBI
  • BCCMA: Predicting TBI Pathology with Visual and Blood-based Biomarkers

 Biography Websites:

Profile at UCSF Neurosurgery

Profile at BMS Graduate Program

Other Resources:

Open Data Commons for Spinal Cord Injury

Open Data Commons for Traumatic Brain Injury